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08/25/2023
MatchXML: An Efficient Text-label Matching Framework for Extreme Multi-label Text Classification
The eXtreme Multi-label text Classification(XMC) refers to training a cl...
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06/09/2023
FLSL: Feature-level Self-supervised Learning
Current self-supervised learning (SSL) methods (e.g., SimCLR, DINO, VICR...
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03/08/2023
M-EBM: Towards Understanding the Manifolds of Energy-Based Models
Energy-based models (EBMs) exhibit a variety of desirable properties in ...
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10/11/2022
APSNet: Attention Based Point Cloud Sampling
Processing large point clouds is a challenging task. Therefore, the data...
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09/16/2022
Towards Bridging the Performance Gaps of Joint Energy-based Models
Can we train a hybrid discriminative-generative model within a single ne...
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08/16/2022
Your ViT is Secretly a Hybrid Discriminative-Generative Diffusion Model
Diffusion Denoising Probability Models (DDPM) and Vision Transformer (Vi...
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03/09/2022
ChiTransformer:Towards Reliable Stereo from Cues
Current stereo matching techniques are challenged by restricted searchin...
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09/19/2021
JEM++: Improved Techniques for Training JEM
Joint Energy-based Model (JEM) is a recently proposed hybrid model that ...
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07/06/2021
Improving Text-to-Image Synthesis Using Contrastive Learning
The goal of text-to-image synthesis is to generate a visually realistic ...
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04/28/2021
Reducing Risk and Uncertainty of Deep Neural Networks on Diagnosing COVID-19 Infection
Effective and reliable screening of patients via Computer-Aided Diagnosi...
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08/30/2020
Adversarial Privacy Preserving Graph Embedding against Inference Attack
Recently, the surge in popularity of Internet of Things (IoT), mobile de...
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12/04/2019
Learning with Multiplicative Perturbations
Adversarial Training (AT) and Virtual Adversarial Training (VAT) are the...
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12/02/2019
Sparse Graph Attention Networks
Graph Neural Networks (GNNs) have proved to be an effective representati...
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08/13/2019
Neural Plasticity Networks
Neural plasticity is an important functionality of human brain, in which...
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04/09/2019
L_0-ARM: Network Sparsification via Stochastic Binary Optimization
We consider network sparsification as an L_0-norm regularized binary opt...
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12/17/2018
Defense-VAE: A Fast and Accurate Defense against Adversarial Attacks
Deep neural networks (DNNs) have been enormously successful across a var...
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12/16/2018
Towards Robust Human Activity Recognition from RGB Video Stream with Limited Labeled Data
Human activity recognition based on video streams has received numerous ...
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11/18/2016
Parallelizing Word2Vec in Multi-Core and Many-Core Architectures
Word2vec is a widely used algorithm for extracting low-dimensional vecto...
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05/31/2016
Extreme Stochastic Variational Inference: Distributed and Asynchronous
We propose extreme stochastic variational inference (ESVI), an asynchron...
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04/15/2016
Parallelizing Word2Vec in Shared and Distributed Memory
Word2Vec is a widely used algorithm for extracting low-dimensional vecto...
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11/21/2015
BlackOut: Speeding up Recurrent Neural Network Language Models With Very Large Vocabularies
We propose BlackOut, an approximation algorithm to efficiently train mas...
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06/09/2015